codeislife99 commented on a change in pull request #7442:
URL: https://github.com/apache/tvm/pull/7442#discussion_r577126119
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File path: python/tvm/relay/op/transform.py
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@@ -1322,6 +1322,71 @@ def adv_index(inputs):
return _make.adv_index(Tuple(inputs))
+def sparse_fill_empty_rows(sparse_indices, sparse_values, dense_shape,
default_value):
+ """
+ Fill first column of the empty rows with default values for a sparse array.
+ It returns a TupleWrapper with 3 outputs
+ Parameters
+ ----------
+ sparse_indices : relay.Expr
+ A 2-D int64 tensor[N, ndims] of integers containing location of sparse
values, where N is
+ the number of sparse values and n_dim is the number of dimensions of
the dense_shape.
+ The inputs for this relay parameter must be in row-major order.
+ sparse_values : relay.Expr
+ A 1-D int64 tensor[N] containing the sparse values for the sparse
indices.
+ dense_shape : relay.Expr
+ A 1-D int64 tensor[ndims] which contains shape of the dense output
tensor.
+ default_value : relay.Expr
+ A 1-D tensor[1] containing the default value for the remaining
locations.
+ Returns
+ -------
+ new_sparse_indices : relay.Expr
+ A 2-D int64 tensor[?, ndims] of integers containing location of new
sparse
+ indices
+ new_sparse_values : relay.Expr
+ A 1-D int64 tensor[?] containing the sparse values for the sparse
indices.
+ empty_row_indicator : relay.Expr
+ A 1-D int64 tensor[dense_shape[0]] filled with zeros and ones
+ indicating whether the particular row is empty or full respectively
+
+ Note:
Review comment:
Done.
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